Getting started with DynamoDB-Mock

DynamoDB is a minimalistic NoSQL engine provided by Amazon as a part of their AWS product.

DynamoDB is great in production environement but sucks when testing your application. Tables needs roughtly 1 min to be created, deleted or updated. Items operation rates depends on how much you pay and tests will conflict if 2 developers run them at the same time.

ddbmock brings a tiny in-memory(tm) implementation of DynamoDB API. It can either be run as a stand alone server or as a regular library helping you to build lightning fast unit and functional tests :)

ddbmock is not intended for production use. It will lose your data. you’ve been warned! I currently recommend the “boto extension” mode for unit-tests and the “server” mode for functional tests.


$ pip install ddbmock

Example usage

Run as Regular client-server

Ideal for test environment. For stage and production I highly recommend using DynamoDB servers. ddbmock comes with no warranty and will loose your data(tm).

Launch the server

$ pserve development.ini # launch the server on

Start the client

import boto
from ddbmock import connect_boto_network

# Use the provided helper to connect your *own* endpoint
db = connect_boto_network()

# Done ! just use it wherever in your project as usual.
db.list_tables() # get list of tables (empty at this stage)

Note: if you do not want to import ddbmock only for the helper, here is a reference implementation:

def connect_boto_network(host='localhost', port=6543):
    import boto
    from boto.regioninfo import RegionInfo
    endpoint = '{}:{}'.format(host, port)
    region = RegionInfo(name='ddbmock', endpoint=endpoint)
    return boto.connect_dynamodb(region=region, port=port, is_secure=False)

Run as a standalone library

Ideal for unit testing or small scale automated functional tests. Nice to play around with boto DynamoDB API too :)

import boto
from ddbmock import connect_boto_patch

# Wire-up boto and ddbmock together
db = connect_boto_patch()

# Done ! just use it wherever in your project as usual.
db.list_tables() # get list of tables (empty at this stage)

Note, to clean patches made in boto.dynamodb.layer1, you can call clean_boto_patch() from the same module.

Advanced usage

A significant part of ddbmock is now configurable through ddbmock.config parameters. This includes the storage backend.

By default, ddbmock has no persitence and stores everything in-memory. Alternatively, you can use the SQLite storage engine but be warned that it will be slower. To switch the backend, you will to change a configuration variable before creating the first table.

from ddbmock import config

# switch to sqlite backend
config.STORAGE_ENGINE_NAME = 'sqlite'
# define the database path. defaults to 'dynamo.db'
config.STORAGE_SQLITE_FILE = '/tmp/my_database.sqlite'

Please note that ddbmock does not persist table metadata currently. As a consequence, you will need to create the tables at each restart even with the SQLite backend. This is hoped to be improved in future releases.

See for a full list of parameters.

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